DocumentCode
1246558
Title
Lifetime distribution based degradation analysis
Author
Chen, Zehua ; Zheng, Shurong
Author_Institution
Dept. of Stat. & Appl. Probability, Nat. Univ. of Singapore, Singapore
Volume
54
Issue
1
fYear
2005
fDate
3/1/2005 12:00:00 AM
Firstpage
3
Lastpage
10
Abstract
The methods commonly used for degradation analysis deduce the lifetime distribution of a product from the distribution of the random parameters in the degradation path model for the product. This approach requires a functional form of the joint distribution of the random parameters, which poses certain practical difficulties. In this paper, we propose an alternative approach which makes inference directly on the lifetime distribution itself. In the proposed approach, degradation data are first used to derive predictive intervals of individual lifetimes. Then an imputation algorithm is invoked to obtain the estimate of the lifetime distribution. The approach has the following advantages: 1) the adequacy of the assumption on the lifetime distribution can be easily examined, 2) the estimated lifetime distribution has a closed form, and 3) the procedure can be more easily implemented. A simulation study is reported to demonstrate the efficiency of the proposed approach. The approach is applied to two real degradation data sets, and compared with Lu-Meeker´s two stage method in the applications.
Keywords
failure analysis; manufactured products; reliability; statistical distributions; degradation analysis; degradation data sets; degradation path model; imputation algorithm; imputation-algorithm; joint distribution; manufactured products; product lifetime distribution; random parameters; reliability; Degradation; Distribution functions; Inference algorithms; Least squares approximation; Life estimation; Lifetime estimation; Maximum likelihood estimation; Mean square error methods; Particle measurements; Time measurement; Degradation; imputation-algorithm; lifetime distribution;
fLanguage
English
Journal_Title
Reliability, IEEE Transactions on
Publisher
ieee
ISSN
0018-9529
Type
jour
DOI
10.1109/TR.2004.837519
Filename
1402674
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